Kazakhstan to integrate AI across the legislative cycle
The Government of Kazakhstan plans to embed Artificial Intelligence into how laws are developed, implemented, and assessed. At a government meeting, Minister of Justice Yerlan Sarsembaev said a specialized AI agent will support the full cycle of legislative drafting and oversight.
The intent is clear: faster drafting, fewer bottlenecks, and tighter feedback loops from real-world outcomes back into policy. The move aims to make legislation more stable, flexible, and efficient while cutting bureaucracy in public administration.
What the AI agent will do
The AI will participate from concept to text: structuring policy options, drafting bill language, and aligning proposals with existing statutes. After adoption, it will help analyze the effectiveness of norms and monitor execution, closing the loop between design and delivery.
This isn't about replacing policy judgment. It's about accelerating work, improving internal consistency, and giving teams better evidence to make decisions.
Progress on reducing bureaucracy
The "package principle" for legislative initiatives has been strengthened to streamline changes. According to the Minister of Justice, 25 laws have already been passed to reduce excessive bureaucracy, with 10 more draft laws now under consideration in Parliament.
Updated legal monitoring
Legal monitoring will now run in a sector-specific format. To date, a comprehensive analysis of 80 sectors of legislation has been completed, creating a clearer picture of overlaps, gaps, and outdated norms.
What this means for ministries and agencies
- Expect shorter drafting cycles and clearer iteration paths across ministries.
- Plan for structured data inputs (laws, by-laws, case practice, regulatory impact assessments) so the AI can work with authoritative sources.
- Prepare for stronger outcome tracking: KPIs tied to each reform, monitored post-implementation.
- Retain human oversight at every step-policy intent, political choices, and public interest remain human-led.
Governance, safeguards, and accountability
- Human-in-the-loop review for all drafts, with clear sign-off roles.
- Traceability: version control, sources cited, and audit trails for each change.
- Fairness and risk checks: bias testing on model outputs, plus red-teaming for sensitive areas.
- Privacy and security: data minimization, classified data handling, and access controls.
- Model lifecycle: validation before deployment, periodic re-evaluation, and documented updates.
Practical steps to prepare
- Identify low-risk pilot areas (technical amendments, harmonization, codification) to prove value.
- Build a cross-functional cell: policy, legal drafting, IT, data, and ethics/compliance.
- Set quality standards: readability, legal consistency, impact traceability, and alignment with higher-order norms.
- Define procurement and evaluation criteria for AI tools (accuracy, explainability, localization, cost, security).
- Create a training plan for civil servants: prompt standards, review checklists, and incident reporting.
- Agree on measurable outcomes: drafting time saved, error rates, compliance costs, and post-enactment results.
Where to look for guidance
For foundational guardrails and good practice in the public sector, see these references:
Upskilling your team
If your unit is planning pilots or scaling AI-assisted drafting, structured upskilling reduces risk and speeds adoption. Explore role-based options here: Complete AI Training - Courses by job.
The direction is set: AI will sit inside the legislative process, not outside it. With the right controls and skills, ministries can move faster, keep quality high, and measure the impact of every reform with more confidence.
Your membership also unlocks:
